import json
import plotly as plotly
import plotly.graph_objects as go

with open('Sample LRS rinnuja.json') as json_file:
    data = json.load(json_file)

print("data tyoe of json statements below: \n" + str(type(data)))
print("length of data: \n " + str(len(data)))
print("statement at index 0: \n " + str(data[0]))
print("acessing key and result in statement at index 0: \n " + str(data[0]['object']['id']))

data tyoe of json statements below: 
<class 'list'>
length of data: 
 21343
statement at index 0: 
 {'actor': {'name': 'canvas test name', 'mbox': 'mailto:canvastestnamehere@gmail.com'}, 'verb': {'id': 'http://adlnet.gov/expapi/verbs/initialized', 'display': {'en-US': 'initialized'}}, 'object': {'id': 'https://elearn.ucr.edu/courses/3730', 'definition': {'name': {'en-US': 'Cal Labs Module 1: Method of Joints'}, 'description': {'en-US': 'Student has started module 1: Method of joints'}, 'type': 'http://adlnet.gov/expapi/activities/course'}, 'objectType': 'Activity'}, 'result': {'duration': 'PT2S'}, 'id': '4e66ecaa-48f6-4b14-b948-f15068983b33', 'timestamp': '2021-06-15T02:14:02.632Z', 'stored': '2021-06-15T02:14:02.632Z', 'authority': {'objectType': 'Agent', 'account': {'homePage': 'https://xcite-testing.lrs.io/keys/authorization', 'name': 'authorization'}}}
acessing key and result in statement at index 0: 
 https://elearn.ucr.edu/courses/3730

Overview

A couple things to consider here.

1) for the items as "canvasdummyname" we have an exported csv with the IP adressses to try to match that 2) We want to show as much data as possible to see where the data gaps are and what we can do so far 3) Then we can decide how to edit the xAPI process

#lets try to get a bar chart that will do show the number of unique actors Y vs verbs X
#iterate thru data and save 
actors = [] #kinda like an list ("array") of strings... idk what the data would be... list?

for eachStatement in data:
    actors.append(eachStatement['actor']['name'])

##print(actors)
#print(actors[0])

verbs = []

for eachStatement in data:
    verbs.append(eachStatement['verb']['display']['en-US'])
#print(verbs)

#using Basic Bar Chart with plotly.graph_objects
fig = go.Figure([go.Bar(x= verbs, y= actors)])
fig.show()
#You do see the bars, but the colors appear grayed out because each bar is composed of hundreds of stacked rectangles with a tiny space between them
#https://stackoverflow.com/questions/66177855/bar-colors-in-plotly-bar-chart-appear-grayed-out

Above graphs probably have to many entries, when need to trim it down.

# using set()
# to remove duplicated 
# from list 
trimmed_actors = list(set(actors))
trimmed_verbs = list(set(verbs))

fig = go.Figure([go.Bar(x= trimmed_verbs, y= trimmed_actors)])
fig.show()

Looks better but still isnt what i want..

timesVisted = [0,0,0,0]

for eachStatement in data:
    for eachVerb in range(4):
        #print(eachVerb) since eachVerb is a string, whenn doing for eachVerb in trimmed_Verbs it doesnt work an index
        if eachStatement['verb']['display']['en-US'] == trimmed_verbs[eachVerb]:
            timesVisted[eachVerb] += 1
        

#print(timesVisted[0])

fig = go.Figure([go.Bar(x= trimmed_verbs, y= timesVisted)])
fig.show()

Checking with Veracity

Here's the data output from veracity makinf each unqiue bar for verb where the matching records is the object id

"data": [ { "_id": "answered", "count": 12971, "canonical": { "display": "answered" }, "value": 12971, "name": "answered", "_category": "answered" }, { "_id": "viewed", "count": 7339, "canonical": { "display": "viewed" }, "value": 7339, "name": "viewed", "_category": "viewed" }, { "_id": "initialized", "count": 677, "canonical": { "display": "initialized" }, "value": 677, "name": "initialized", "_category": "initialized" }, { "_id": "exited", "count": 338, "canonical": { "display": "exited" }, "value": 338, "name": "exited", "_category": "exited" } ]

Only viewed is slightly off is this is due to the fact that some tests where done after I downloaded the json data

plotly.offline.init_notebook_mode()